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										01. 多线程基础
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										03. synchronized
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										04. AQS和ReentrantLock
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										05. 线程池
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										06. ThreadLocal
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										07. CountDownLatch和CyclicBarrier
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										08. 为什么需要Java内存模型
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										09. 深入浅出Java内存模型
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										03-Java容器
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										01. List集合
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										02. Map集合
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										04-Java虚拟机
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										01. Java编译到执行的过程
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										02. 双亲委派机制
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										03. JVM内存结构
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										04. 垃圾回收机制
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										05. CMS垃圾收集器
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										06. G1垃圾收集器
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										07. JVM调优
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										05-Spring
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										01. SpringMVC
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										02. Spring基础
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										03. SpringBean生命周期
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										01. Redis基础
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										02. Redis持久化
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										03. Redis主从架构
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										04. Redis分片集群
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										07-消息队列
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										01. Kafka基础
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										02. 使用Kafka会考虑什么问题
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										08-MySQL
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										01. MySQL索引
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										02. MySQL事务和锁机制和MVCC
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										03. MySQL调优
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										09-项目场景类
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										01. 如何实现去重和幂等
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										02. 系统需求多变如何设计
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										03. 设计模式
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										10-计算机网络
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										01. HTTP
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										11-算法
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										01. 排序算法
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	01. Kafka基础
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	<span>3y</span>
	<span>2021-08-19 16:03:42</span>
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	<p><span style="color:#ab4642"><strong>面试官</strong></span>：<strong>今天要不来聊聊消息队列吧？我看你项目不少地方都写到Kafka了</strong></p>
<p><span style="color:#000080"><strong>候选者</strong></span>：嗯嗯</p>
<p><span style="color:#ab4642"><strong>面试官</strong></span>：<strong>那你简单说明下你使用Kafka的场景吧</strong></p>
<p><span style="color:#000080"><strong>候选者</strong></span>：使用消息队列的目的总的来说可以有三种情况：解耦、异步和削峰</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：比如举我项目的例子吧，我现在维护一个消息管理平台系统，对外提供接口给各个业务方调用</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：他们调用接口之后，实际上『不是同步』下发了消息。</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：在接口处理层只是把该条消息放到了消息队列上，随后就直接返回结果给接口调用者了。</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：这样的好处就是：</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：1. 接口的吞吐量会大幅度提高（因为未做真正实际调用，接口RT会非常低）【异步】</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：2. 即便有大批量的消息调用接口都不会让系统受到影响（流量由消息队列承载）【削峰】</p>
<p><img src="https://tva1.sinaimg.cn/large/008i3skNgy1gtzr8lpu0mj60y006kdgz02.jpg"></p>
<p><span style="color:#000080"><strong>候选者</strong></span>：又比如说，我这边还有个项目是广告订单归因工程，主要做的事情就是得到订单数据，给各个业务广告计算对应的佣金。</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：订单的数据是从消息队列里取出的</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：这样设计的好处就是：</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：1. 交易团队的同学只要把订单消息写到消息队列，该订单数据的Topic由各个业务方自行消费使用【解耦】【异步】</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：2. 即便下单QPS猛增，对下游业务无太大的感知（因为下游业务只消费消息队列的数据，不会直接影响到机器性能）【削峰】</p>
<p><span style="color:#ab4642"><strong>面试官</strong></span>：嗯，那我想问下，<strong>你觉得为什么消息队列能到削峰？</strong></p>
<p><span style="color:#ab4642"><strong>面试官</strong></span>：或者换个问法，<strong>为什么Kafka能承载这么大的QPS？</strong></p>
<p><span style="color:#000080"><strong>候选者</strong></span>：消息队列「最核心」的功能就是把生产的数据存储起来，然后给各个业务把数据再读取出来。</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：跟我们处理请求时不一样：在业务处理时可能会调别人的接口，可能会需要去查数据库…等等等一系列的操作才行</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：像Kafka在「存储」和「读取」这个过程中又做了很多的优化</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：举几个例子，比如说：</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：我们往一个Topic发送消息或者读取消息时，实际内部是多个Partition在处理【并行】</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：在存储消息时，Kafka内部是顺序写磁盘的，并且利用了操作系统的缓冲区来提高性能【append+cache】</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：在读写数据中也减少CPU拷贝文件的次数【零拷贝】</p>
<p><img src="https://tva1.sinaimg.cn/large/008i3skNgy1gtzr9nblz8j61bq06stae02.jpg"></p>
<p><span style="color:#ab4642"><strong>面试官</strong></span>：<strong>嗯，你既然提到减少CPU拷贝文件的次数，可以给我说下这项技术吗？</strong></p>
<p><span style="color:#000080"><strong>候选者</strong></span>：嗯，可以的，其实就是零拷贝技术。</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：比如我们正常调用read函数时，会发生以下的步骤:</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：1. DMA把磁盘的拷贝到读内核缓存区</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：2. CPU把读内核缓冲区的数据拷贝到用户空间</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：正常调用write函数时，会发生以下的步骤：</p>
<p><span style="color:#000080"><strong>候选者</strong></span>:  1. CPU把用户空间的数据拷贝到Socket内核缓存区</p>
<p><span style="color:#000080"><strong>候选者</strong></span>:  2. DMA把Socket内核缓冲区的数据拷贝到网卡</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：可以发现完成「一次读写」需要2次DMA拷贝，2次CPU拷贝。而DMA拷贝是省不了的，所谓的零拷贝技术就是把CPU的拷贝给省掉</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：并且为了避免用户进程直接操作内核，保证内核安全，应用程序在调用系统函数时，会发生上下文切换（上述的过程一共会发生4次）</p>
<p><img src="https://tva1.sinaimg.cn/large/008i3skNgy1gtt04u807kj614m0r077a02.jpg"></p>
<p><span style="color:#000080"><strong>候选者</strong></span>：目前零拷贝技术主要有：mmap和sendfile，这两种技术会一定程度下减少上下文切换和CPU的拷贝</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：比如说：mmap是将读缓冲区的地址和用户空间的地址进行映射，实现读内核缓冲区和应用缓冲区共享</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：从而减少了从读缓冲区到用户缓冲区的一次CPU拷贝</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：使用mmap的后一次读写就可以简化为：</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：一、DMA把硬盘数据拷贝到读内核缓冲区。</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：二、CPU把读内核缓存区拷贝至Socket内核缓冲区。</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：三、DMA把Socket内核缓冲区拷贝至网卡</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：由于读内核缓冲区与用户空间做了映射，所以会省了一次CPU拷贝</p>
<p><img src="https://tva1.sinaimg.cn/large/008i3skNgy1gtzrkvs0j8j610s0r4tbm02.jpg"></p>
<p><span style="color:#000080"><strong>候选者</strong></span>：而sendfile+DMA Scatter/Gather则是把读内核缓存区的文件描述符/长度信息发到Socket内核缓冲区，实现CPU零拷贝</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：使用sendfile+DMA Scatter/Gather一次读写就可以简化为：</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：一、DMA把硬盘数据拷贝至读内核缓冲区。</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：二、CPU把读缓冲区的文件描述符和长度信息发到Socket缓冲区。</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：三、DMA根据文件描述符和数据长度从读内核缓冲区把数据拷贝至网卡</p>
<p><img src="https://tva1.sinaimg.cn/large/008i3skNgy1gtzrmwsi09j611c0psacp02.jpg"></p>
<p><span style="color:#000080"><strong>候选者</strong></span>：回到Kafka上</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：从Producer-&gt;Broker，Kafka是把网卡的数据持久化硬盘，用的是mmap（从2次CPU拷贝减至1次）</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：从Broker-&gt;Consumer，Kafka是从硬盘的数据发送至网卡，用的是sendFile（实现CPU零拷贝）</p>
<p><span style="color:#ab4642"><strong>面试官</strong></span>：我稍微打断下，我还有点事忙，我总结下你说的话吧</p>
<p><span style="color:#ab4642"><strong>面试官</strong></span>：你用Kafka的原因是为了异步、削峰、解耦</p>
<p><span style="color:#ab4642"><strong>面试官</strong></span>：Kafka能这么快的原因就是实现了并行、充分利用操作系统cache、顺序写和零拷贝</p>
<p><span style="color:#ab4642"><strong>面试官</strong></span>：没错吧？</p>
<p><span style="color:#000080"><strong>候选者</strong></span>：嗯</p>
<p><span style="color:#ab4642"><strong>面试官</strong></span>：ok，下次继续面吧， 我这边有点忙</p>
<p><img src="https://tva1.sinaimg.cn/large/008i3skNgy1gtm5u0x7d9j61400mi77702.jpg"></p>
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